Slides from my presentation this morning to this group of cancer communicators at their annual meeting in Columbus, Ohio.

1. Lee Aase (@LeeAase)
Mayo Clinic Center for Social Media
April 26, 2014
#NACCDOPAN
Strategic Application of Digital Media
in Oncology Marketing and
Communications

2. When we were last together...

3. THE Book on Social Media in Health
Care
• Essays from 30 thought
leaders
• The “Why?” of social media
in health care
• Net proceeds fund patient
scholarships
• Available on Amazon and
discount bulk orders on
CreateSpace (with offer
code Z4L7DBSN)

5. Agenda
• What’s happened since April 2009
• Making marketing and communications better
through social and digital platforms
• Demonstrating bottom-line benefits

6. The revolutionary impact of
consumer-grade video

8. Dramatically increased number of videos
and depth of content

13. YouTube Playlists

14. YouTube Playlists

15. YouTube Playlists

16. A Case Study in Media Synergy

20. My Excellent Phillies Adventure

34. Social and Traditional Media Synergy
• YouTube video leads to USA Today story
• USA Today story leads to #wristpain Twitter chat
with explanatory videos and trainee list
• Twitter chat leads to patient procedure and blog
post
• Blog post leads to USA Today story

35. Twitter Chats Today
• Social Media/Media Relations combo
• Typically 3-4 chats per week with Mayo experts
• Reach consumers/patients directly and cultivate
journalist relationship
• #MayoUSAToday (circa 2009-2010)
• #ABCDrBChat

36. TW 110: How to Effectively Participate in a Twitter Chat

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39. A 2009 Email from Dr. Noseworthy
• Paraphrased version: I know we’re doing a lot in
social media, but have we considered whether
a bigger investment is warranted?
• January 2010 meeting Dr. Noseworthy and
Shirley Weis endorsed concept of Center for
Social Media
• Planning team from across Mayo gathered
• Announced MCCSM in July 2010

40. Mayo Clinic Center for Social Media
• The Mayo Clinic Center for Social Media exists
to improve health globally by accelerating
effective application of social media tools
throughout Mayo Clinic and spurring broader
and deeper engagement in social media by
hospitals, medical professionals and patients.
• Our Mission: Lead the social media revolution in
health care, contributing to health and well
being for people everywhere.

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A Catalyst for Social Media

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43. Social Media Health Network
• Membership group associated with Mayo Clinic
Center for Social Media
• For organizations wanting to use social media to
promote health, fight disease and improve
health care
• Much content available through free Guest
account
• Dues based on organization revenues, and
individual paid memberships also are available

45. Measuring the Benefits of Social Media:
Reuben Mesa, M.D. and Myelofibrosis

47. Unique Myelofibrosis Patients
0
100
200
300
400
2008 2009 2010 2011 2012 2013
MCF MCA

52. Impact of Videos
• The Data
• 3 Videos
• 23:11 Total Running Time
• 4,959 Total Views
• The Benefits
• Time saving in office explanations
• Elevating quality of patient conversations
• Increased patient volumes
• Enhanced professional stature among peers

53. Lee’s Social Media
Measurement Maxim:
As I approaches 0, ROI approaches
∞

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Big Ideas
• Measurement only matters in the context of
making or evaluating a decision
• Measurement reduces uncertainty and the
risk of being wrong
• A little measurement can give you a big
reduction in uncertainty

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One Quick Uncertainty-Reducing
Method: The Rule of 5
• Random sample of 5 values
• High and low valutes give you 93.75%
confidence interval (CI) of the median
• In a normal distribution, median and mean
will be the same

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Case Study:
“Massive” Exercise in
Salt Lake City

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Research Exercise
• Enter your weight in pounds. Feel free to round
down to the nearest 5.
• Enter the lower and upper bounds for your
estimate of the average (mean) weight for
everyone in the course.
• “I am 90 percent certain that the average weight
of people in this room is between ____ and ____
pounds.”

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Review of Results
• Smallest range guessed: 10 (150-160 and 165-175)
• Largest range guessed 195 (100-295)
• Percent of those including the mean: 83%
• Average range of those including mean: 93.7
• Average range of those not including mean: 35.0
• Actual Mean for Population: 167.2

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n=5 n=8 n=11
155 100 100
165 115 115
175 155 135
220 165 145
250 175 155
200 165
220 175
250 180
200
220
250

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“Mathless” CIs for Small Samples
Sample
Size (n)
_th smallest
_th largest
Confidence
5 1st 93.75%
8 2nd 93.0%
11 3rd 93.5%
13 4th 90.8%
16 5th 92.3%

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n=5 n=8 n=11
155 100 100
165 115 115
175 155 135
220 165 145
250 175 155
200 165
220 175
250 180
200
220
250

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n=5 n=8 n=11
155 100 100
165 115 115
175 155 135
220 165 145
250 175 155
200 165
220 175
250 180
200
220
250

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Lessons
• If you have a lot of uncertainty, just a few
measurements can tell you a lot
• The Mathless Method can get you a quick
answer that is better than most expert
estimates
• In this case, sampling produced better ranges
• n=5 produced a better range than 49 of 87
• n=11 produced a better range nearly 3X as
often as human guessing did (63 vs. 23)

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Unraveling the Fermi Decomposition
• Named after Nobel Prize winner Enrico Fermi
• For a big unknown, break the problem into
components you can measure or more
confidently estimate
• Classic question: How many piano tuners are
in Chicago?

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Number of Piano Tuners =
Population/people per household
x percent of households w/tuned pianos
x tunings per piano per year
/(tunings per tuner per day x workdays
per year)

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Develop Your 90% CI
• For each formula component, estimate the 90
percent confidence interval through
• Calibrated estimates of experts
• Rules of thumb/historical performance
• Surveys and sampling
• Direct measures where practical

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Monte Carlo Simulation
• Run a large number of calculations (5,000 to
10,000) with randomly generated values for
each variable, based on your 90% CI
• Expected outcome = value x probability

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Disclaimer:
All Numbers in the Following
Example are Hypothetical!

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Example: Adding staffer for
demand-generating videos
• Proposal is to hire an employee to shoot, edit
and upload videos to YouTube and add
annotations linking to appointment request
page, along with a phone number
• Goal is to increase demand in areas of practice
with favorable reimbursement
• Is this likely to generate demand that would pay
for the new employee?

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Break it down like Fermi
• Costs = Salary & Benefits + equipment +
software + travel
• Annual Benefit =
• NOI per patient x
• Number of New Patients

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Continuing the Decomposition
Annual Benefit =
NOI/Patient
x Patients/Video
x Videos/Week
x Weeks/Year

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Continuing the Decomposition
Annual Benefit =
NOI/Patient
x Patients/Video
x Videos/Week
x Weeks/Year

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Continuing the Decomposition
Annual Benefit =
NOI/Patient
x Patients/Video
x Videos/Week
x Weeks/Year
Annual Benefit =
NOI/Patient
x Patients/View
x Views/Video
x Videos/Week
x Weeks/Year

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Continuing the Decomposition
Annual Benefit =
NOI/Patient
x Patients/Video
x Videos/Week
x Weeks/Year
Annual Benefit =
NOI/Patient
x Patients/View
x Views/Video
x Videos/Week
x Weeks/Year

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Completing the Decomposition
Annual Benefit =
NOI/Patient
x Views/Video
x Patients/View
x Videos/Week
x Weeks/Year
Annual Benefit =
NOI/Patient
x Views/Video
x Clicks to Web Site/View
x (Online Appt Reqs/View
+ Phone Req/View)
x Patients/Appt Req
x Videos/Week
x Weeks/Year

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Developing the 90% CI
• How might you estimate
• Weeks per year worked by new employee?
• Average videos produced per week?
• Views per video?
• Annotation clicks per view?
• Appointment requests per annotation click?
• Phone appointment requests related to videos?
• Percent of requests likely to be fulfilled?
• NOI per patient?

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Do the Monte Carlo Simulation
• Apply the formula in 10,000 simulations with
random values from your 90% CI
• Videos/week (8-12)
• Weeks worked/year (48-50)
• Views/Video (500-1500)
• Annotation Clicks/Video View (.005-.02)
• Online appointment requests/annotation click
(0.01-0.03)
• Phone appointment requests/annotation click
(0.01-0.03)
• Appointments scheduled/request (0.5-0.8)
• NOI/Patient ($400-$800)

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Monte Carlo Simulation

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Monte Carlo Simulation

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Monte Carlo Simulation

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Monte Carlo Simulation

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• If it’s really that important, it’s something
you can define. If it’s something you think
exists at all, it’s something you’ve already
observed somehow
• If it’s something important and something
uncertain, you have a cost of being wrong
and a chance of being wrong
• You can quantify your current uncertainty
with calibrated estimates
Summary of Philosophy

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Summary of Philosophy
• You can compute the value of additional
information by knowing the “threshold” of the
measurement where it begins to make a
difference compared to your existing uncertainty.
• Once you know what it is worth to measure
something, you can put the measurement effort in
context and decide on the effort it should take.
• Knowing just a few methods for random sampling,
controlled experiments, Bayesian methods or
even merely improving on the judgments of
experts can lead to a significant reduction in
uncertainty.

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Simulate Before AND After
• Lack of CRM perfection isn’t insurmountable
barrier to demonstrating ROI
• Get stakeholder/leadership agreement on CIs
• Refine measurements and CIs based on
ongoing experience. Iterate!

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Other Measurement
Applications
• Adding a blog version of a print newsletter
• Better gauge of readership by adding
interaction
• Estimate costs/benefits of reducing print
• Building seminar attendance through
• Traditional methods (including advertising)
• Facebook ads

91. Practical Example:
Patient Education Collaboration Opportunities
• Videos covering FAQs
• Short, procedurally focused videos are ideal
• Huge potential savings - competing vs. non-
production
• Crossover potential for demand generation

94. Calculating ROI
• Cost of shooting and editing < $200
• Cost of storage: $0
• Cost of distribution: $0
• Value of time saved: $?,???
• Develop 90% CIs for each variable
• NG pts/year x minutes/pt x $/hr/60 x self-
serve %
• Run a Monte Carlo simulation
• Increase in patient satisfaction: $?,???
• Other “marketing” benefits: $?

95. Applying Capabilities
• Mayo Clinic Connect community
• Mayo Clinic News Network
• Adding interaction and bonus features to
publications
• Research
• Recruitment for clinical trials
• Therapeutic applications
• Education
• Continuing education promotion
• Integration within courses

108. For Further Interaction:
• Google Lee Aase or MCCSM
• @LeeAase on Twitter
• For Social Media Health Network information
• http://network.socialmedia.mayoclinic.org/
mccsm/joining-the-network/
• Contact Mayo Clinic Center for Social Media
• By email: socialmediacenter@mayo.edu
• By phone: 507-538-1091